TSNE plots of the data.

Remove bad quality cluster 1 from the data.

data_cleaned <- SubsetData(data, cells.use=rownames(data@meta.data)[data@meta.data$res.0.5 != 1])
TSNEPlot(data_cleaned, group.by='res.0.5', pt.size=0.1)

Save the cleaned up Seurat object to run preprocessing again (new PCA, clustering and tSNE).

#saveRDS(data_cleaned, 'output/10x-180831')

Figures

sfig <- plot_grid(
 t4,
 t1,
 t2,
 t3,
 nrow=2, labels='auto'
)
#save_plot('plots/supplementary_figures/sfig_180831_bad-quality-cluster.pdf', sfig, base_width=12, base_height = 9)
sfig

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